Self learning machine learning transaction scores adjustment via normalization thereof accounting for underlying transaction score bases

Provided are a system and methodology for iteratively transforming data, as between multiple sets thereof, that account for underlying data generation sources and bases. Doing so, via normalization of the data, enables uniformity of interpretation and presentation of the data no matter the machine learning model that produced the data.